The present invention disclosed herein relates to a method of recommending stickers during a dialogue through a social network service or an instant messenger, and more particularly, to a method of recommending a responsive sticker to respond to an utterance of the other party.
Emoticons are being used to express the emotional state of a user during a dialogue through a social network service or an instant messenger.
In the past, emoticons (e.g., OTL, TT, ^^; etc.) written with texts was added to the end of the utterance, but in recent years, emoticons of graphic image types are being widely used.
While inputting dialogue contents, a user opens an emoticon selection window and then selects and inputs an appropriate emoticon. In order to more conveniently perform the foregoing process, a technology of automatically converting and expressing a text inputted by a user into an emoticon has been also developed.
FIG. 1 is a view illustrating an emoticon displayed on a well-known personal computer messenger (NateOn).
In the well-known messenger shown in FIG. 1, when a specific keyword is inputted, the corresponding text is automatically converted into an emoticon corresponding to the specific keyword. In FIG. 1, when a user inputs a word “present”, it can be seen that the word “present” is automatically converted into the emotion corresponding to the present.
However, when a specific keyword is simply inputted, this related art technology merely expresses an emoticon matched with the specific keyword in advance. Accordingly, in many cases, emoticons are expressed in regardless of dialogue contents or contexts and emotional state, even in an inappropriate manner in the light of the dialogue situation.
In order to overcome these limitations, Korean Patent Application Publication No. 10-2011-0026218 discloses “apparatus and method for inputting text message and its program stored in recording medium”, which extract words indicating the emotional state from dialogue contents that are inputted, and select an emoticon matching with the emotional state using the extracted words.
However, this technology is also merely to match the keyword with the corresponding emoticon one-to-one by analyzing inputted texts when keywords representing the emotional state such as happiness and sadness show.
Accordingly, since the context or dialogue situation and relationship between users are not considered, inappropriate emoticons may be recommended.
In addition, the paper published in Korean Computer Conference, by Jun-Hyuk Kim et al., 2014, entitled “Automated Emotion Recommendation Module Based on Bigram-Signature Using Text Mining” discloses a technology of more accurately extracting keywords for recommending emoticons by parsing Korean sentences using bigram.
However, the technology disclosed in the paper also provides only one-to-one matching of a keyword and an emoticon, and has a limitation in that an appropriate emoticon cannot be recommended in consideration of the situation or context of dialogue.
Particularly, the foregoing technology is merely to analyze utterances of users-dialogue contents-themselves and recommend emoticons corresponding thereto, and has a limitation in that emoticons for appropriately responding to utterances of the other party cannot be recommended.